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Matej MihelÄiÄ‡

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Rating prediction query datasets

Created: 2012-01-29 17:05:46 | Last updated: 2012-01-29 17:07:49

Credits: tomS

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This is a file containing query sets for online updates of rating prediction operators.

File type: application/x-zip-compressed

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Matej MihelÄiÄ‡

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Item recommendation query datasets

Created: 2012-01-29 17:02:50 | Last updated: 2012-01-30 13:20:16

Credits: tomS

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This is a file containing query datasets for online updates of item recommendation operators.

File type: application/x-zip-compressed

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Matej MihelÄiÄ‡

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Help for using experimentation workflows with recomm...

Created: 2012-01-29 11:59:49 | Last updated: 2012-01-29 17:28:20

Credits: Matej MihelÄiÄ‡

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This is a help file in how to use experimentation workflows with a recommendation operators.

File type: application/publicationlist

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Matej MihelÄiÄ‡

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Data example for experimentation with recommender ex...

Created: 2012-01-29 11:53:41 | Last updated: 2012-01-30 13:19:23

Credits: tomS

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This is a train/test set example used in experimentation. Data in this set consists of three columns, one column for user identification, one for item identification, and one for rating. Every dataset is accompanied with the appropriate aml file. This dataset can be used for rating prediction and item recommendation operator testing. Item recommendation operators will ignore the rating column.

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Matko BoÅ¡njak

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Experimental user to item score matrix Excel file

Created: 2011-11-26 20:07:02 | Last updated: 2011-11-26 20:07:04

Credits: Matko BoÅ¡njak

License: Creative Commons Attribution-Share Alike 3.0 Unported License

A test file for Collaborative filtering recommender

File type: Excel workbook

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Taverna 2

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James Eales

One sentence per line (1)

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This workflow accepts a plain text input and provides a single text document per input containing one sentence per line. Newline characters are removed from the original input. The OpenNLP sentence splitter is used to split the text, this is provided by University of Manchester Web Services.